------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
       log:  C:\Users\drj3\Desktop\AYCEOut.log
  log type:  text
 opened on:  26 Sep 2009, 22:14:11

. do "C:\Users\drj3\AppData\Local\Temp\STD00000000.tmp"

. * Load Data
. insheet using "C:\Users\drj3\Desktop\Pizza Garden Survey-2007.txt"
(22 vars, 66 obs)

. 
. * Define some additional variables
. gen dolperslice=5.98/actualeat if coupon1==0
(31 missing values generated)

. replace dolperslice=2.99/actualeat if coupon==1
(31 real changes made)

. gen actualcalories=actualeat*358

. gen fat=actualeat*13

. gen platewaste=actualtake-actualeat

. gen heightm=(12*heightft+heightin)*.0254
(1 missing value generated)

. 
. *Sort data for summary statistics
. sort coupon

. 
. *Summary statistics for table 1
. by coupon: sum actualtake actualeat dolperslice actualcalories fat platewaste esteat eatcal typeeat generalgreat firstgreat lastgreat highquality satquality satquantity moreshould moneysworth age gender
>  heightm number

_______________________________________________________________________________
-> coupon1 = 0

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  actualtake |        35        4.52      2.3947          1         11
   actualeat |        35        4.09    1.948899          1        9.1
 dolperslice |        35    1.976987    1.399231   .6571428       5.98
actualcalo~s |        35     1464.22    697.7057        358     3257.8
         fat |        35       53.17    25.33568         13      118.3
-------------+--------------------------------------------------------
  platewaste |        35         .43    .6510399          0          2
      esteat |        35    4.171429    2.021731          1         10
      eatcal |        31    697.2581    467.5358         45       2000
     typeeat |        34        5.75    6.240447          1         40
generalgreat |        35    6.257143    1.521278          2          9
-------------+--------------------------------------------------------
  firstgreat |        35    6.514286    1.669298          2          9
   lastgreat |        35    6.485714    1.560004          2          9
 highquality |        35         5.6    1.575548          2          9
  satquality |        35           6    1.212678          4          9
 satquantity |        33    6.454545    1.660025          2          9
-------------+--------------------------------------------------------
  moreshould |        35    5.142857    2.840286          1          9
 moneysworth |        33    7.242424    2.000473          1          9
         age |        35    36.17143    11.79353         17         58
      gender |        35    .8571429    .3550358          0          1
     heightm |        34    1.794809     .085436     1.5748     1.9431
-------------+--------------------------------------------------------
      number |        35    4.428571    1.667787          2          7

_______________________________________________________________________________
-> coupon1 = 1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  actualtake |        31     3.16129    2.083215          1         11
   actualeat |        31    2.945161    1.658481          1        8.6
 dolperslice |        31    1.330541    .7386529   .3476744       2.99
actualcalo~s |        31    1054.368    593.7362        358     3078.8
         fat |        31     38.2871    21.56025         13      111.8
-------------+--------------------------------------------------------
  platewaste |        31     .216129    .5342263          0        2.4
      esteat |        31           3    1.825742          1         10
      eatcal |        25       715.6    667.6955         30       3000
     typeeat |        31    3.935484    1.400845          1          8
generalgreat |        30    6.866667    1.676065          3          9
-------------+--------------------------------------------------------
  firstgreat |        31    7.096774    1.468669          5          9
   lastgreat |        31    6.709677    1.636939          3          9
 highquality |        31     6.16129    1.753031          1          9
  satquality |        30    6.433333    1.356551          4          9
 satquantity |        31    6.741935    1.652629          3          9
-------------+--------------------------------------------------------
  moreshould |        30         5.2    2.808853          1          9
 moneysworth |        31    7.096774     1.97239          1          9
         age |        31    34.03226    12.74228          7         62
      gender |        31    .7419355    .4448027          0          1
     heightm |        31    1.757926    .1554657     1.2192     2.1082
-------------+--------------------------------------------------------
      number |        31    3.967742    1.516221          1          6


. 
. * Test statistics for table 1
. oneway actualtake coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      30.3486332      1   30.3486332      5.97     0.0173
 Within groups      325.169548     64   5.08077419
------------------------------------------------------------------------
    Total           355.518181     65   5.46951048

Bartlett's test for equal variances:  chi2(1) =   0.6039  Prob>chi2 = 0.437

. oneway actualeat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      21.5463845      1   21.5463845      6.52     0.0131
 Within groups      211.655782     64    3.3071216
------------------------------------------------------------------------
    Total           233.202167     65   3.58772564

Bartlett's test for equal variances:  chi2(1) =   0.8082  Prob>chi2 = 0.369

. oneway dolperslice coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      6.86988388      1   6.86988388      5.30     0.0246
 Within groups      82.9350806     64   1.29586063
------------------------------------------------------------------------
    Total           89.8049644     65   1.38161484

Bartlett's test for equal variances:  chi2(1) =  11.7357  Prob>chi2 = 0.001

. oneway actualcalories coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      2761470.82      1   2761470.82      6.52     0.0131
 Within groups      27126651.1     64   423853.923
------------------------------------------------------------------------
    Total           29888121.9     65    459817.26

Bartlett's test for equal variances:  chi2(1) =   0.8082  Prob>chi2 = 0.369

. oneway fat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups        3641.339      1     3641.339      6.52     0.0131
 Within groups      35769.8267     64   558.903542
------------------------------------------------------------------------
    Total           39411.1657     65   606.325626

Bartlett's test for equal variances:  chi2(1) =   0.8082  Prob>chi2 = 0.369

. oneway platewaste coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       .75195092      1    .75195092      2.09     0.1527
 Within groups      22.9729327     64   .358952074
------------------------------------------------------------------------
    Total           23.7248836     65    .36499821

Bartlett's test for equal variances:  chi2(1) =   1.2094  Prob>chi2 = 0.271

. 
. oneway esteat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      22.5588745      1   22.5588745      6.04     0.0167
 Within groups      238.971429     64   3.73392857
------------------------------------------------------------------------
    Total           261.530303     65   4.02354312

Bartlett's test for equal variances:  chi2(1) =   0.3244  Prob>chi2 = 0.569

. oneway eatcal coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       4655.9038      1    4655.9038      0.01     0.9044
 Within groups      17257307.9     54   319579.777
------------------------------------------------------------------------
    Total           17261963.8     55   313853.888

Bartlett's test for equal variances:  chi2(1) =   3.3417  Prob>chi2 = 0.068

. oneway typeeat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      53.3886476      1   53.3886476      2.50     0.1187
 Within groups      1343.99597     63   21.3332693
------------------------------------------------------------------------
    Total           1397.38462     64   21.8341346

Bartlett's test for equal variances:  chi2(1) =  50.9123  Prob>chi2 = 0.000

. 
. oneway generalgreat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       6.0014652      1    6.0014652      2.36     0.1294
 Within groups      160.152381     63   2.54210128
------------------------------------------------------------------------
    Total           166.153846     64   2.59615385

Bartlett's test for equal variances:  chi2(1) =   0.2903  Prob>chi2 = 0.590

. oneway firstgreat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.57776847      1   5.57776847      2.24     0.1395
 Within groups      159.452535     64   2.49144585
------------------------------------------------------------------------
    Total           165.030303     65   2.53892774

Bartlett's test for equal variances:  chi2(1) =   0.5104  Prob>chi2 = 0.475

. oneway lastgreat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      .824591537      1   .824591537      0.32     0.5715
 Within groups      163.129954     64   2.54890553
------------------------------------------------------------------------
    Total           163.954545     65   2.52237762

Bartlett's test for equal variances:  chi2(1) =   0.0728  Prob>chi2 = 0.787

. oneway highquality coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.17917889      1   5.17917889      1.88     0.1755
 Within groups      176.593548     64   2.75927419
------------------------------------------------------------------------
    Total           181.772727     65    2.7965035

Bartlett's test for equal variances:  chi2(1) =   0.3585  Prob>chi2 = 0.549

. 
. oneway satquality coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      3.03333333      1   3.03333333      1.85     0.1788
 Within groups      103.366667     63   1.64074074
------------------------------------------------------------------------
    Total                106.4     64       1.6625

Bartlett's test for equal variances:  chi2(1) =   0.3887  Prob>chi2 = 0.533

. oneway satquantity coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      1.32019795      1   1.32019795      0.48     0.4905
 Within groups      170.117302     62   2.74382745
------------------------------------------------------------------------
    Total             171.4375     63   2.72123016

Bartlett's test for equal variances:  chi2(1) =   0.0006  Prob>chi2 = 0.980

. oneway moreshould coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      .052747253      1   .052747253      0.01     0.9355
 Within groups      503.085714     63   7.98548753
------------------------------------------------------------------------
    Total           503.138462     64   7.86153846

Bartlett's test for equal variances:  chi2(1) =   0.0038  Prob>chi2 = 0.951

. oneway moneysworth coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       .33909152      1    .33909152      0.09     0.7704
 Within groups      244.770283     62    3.9479078
------------------------------------------------------------------------
    Total           245.109375     63     3.890625

Bartlett's test for equal variances:  chi2(1) =   0.0061  Prob>chi2 = 0.938

. 
. oneway age coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      75.2274962      1   75.2274962      0.50     0.4814
 Within groups      9599.93917     64    149.99905
------------------------------------------------------------------------
    Total           9675.16667     65   148.848718

Bartlett's test for equal variances:  chi2(1) =   0.1883  Prob>chi2 = 0.664

. oneway gender coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      .218195783      1   .218195783      1.37     0.2468
 Within groups      10.2211982     64   .159706221
------------------------------------------------------------------------
    Total           10.4393939     65   .160606061

Bartlett's test for equal variances:  chi2(1) =   1.5961  Prob>chi2 = 0.206

. oneway heightm coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      .022058696      1   .022058696      1.44     0.2348
 Within groups      .965964229     63   .015332766
------------------------------------------------------------------------
    Total           .988022926     64   .015437858

Bartlett's test for equal variances:  chi2(1) =  10.6701  Prob>chi2 = 0.001

. oneway number coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      3.49113252      1   3.49113252      1.37     0.2468
 Within groups      163.539171     64   2.55529954
------------------------------------------------------------------------
    Total           167.030303     65   2.56969697

Bartlett's test for equal variances:  chi2(1) =   0.2833  Prob>chi2 = 0.595

. 
. *exact permutation test for text describing table 1
. oneway actualeat coupon1

                        Analysis of Variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      21.5463845      1   21.5463845      6.52     0.0131
 Within groups      211.655782     64    3.3071216
------------------------------------------------------------------------
    Total           233.202167     65   3.58772564

Bartlett's test for equal variances:  chi2(1) =   0.8082  Prob>chi2 = 0.369

. permute coupon1 "oneway actualeat coupon1" F=r(F), reps(10000)

command:      oneway actualeat coupon1
statistic:    F          = r(F)
permute var:  coupon1

Warning:  Since oneway is not an estimation command or does not set e(sample), permute has no way to determine which observations are used in calculating the statistics and so assumes that all
          observations are used.  This means no observations will be excluded from the resampling due to missing values or other reasons.

          If the assumption is not true, press Break, save the data, and drop the observations that are to be excluded.  Be sure the dataset in memory contains only the relevant data.


Monte Carlo permutation statistics                Number of obs    =        66
                                                  Replications     =     10000

------------------------------------------------------------------------------
T            |     T(obs)       c       n   p=c/n   SE(p) [95% Conf. Interval]
-------------+----------------------------------------------------------------
F            |   6.515147     127   10000  0.0127  0.0011  .0105981   .0150923 
------------------------------------------------------------------------------
Note:  confidence interval is with respect to p=c/n
Note:  c = #{|T| >= |T(obs)|}

. 
. * Minimum distance matching estimators for table 2
. nnmatch actualeat coupon1 age gender heightm number, robust(1)
1 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        65
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |  -1.128462   .3867987    -2.92   0.004    -1.886573     -.37035
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. nnmatch dolperslice coupon1 age gender heightm number, robust(1)
1 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        65
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
 dolperslice |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |  -.5764728   .2211163    -2.61   0.009    -1.009853   -.1430928
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. nnmatch generalgreat coupon1 age gender heightm number, robust(1)
2 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        64
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
generalgreat |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |      .6875   .4180478     1.64   0.100    -.1318587    1.506859
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. nnmatch firstgreat coupon1 age gender heightm number, robust(1)
1 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        65
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
  firstgreat |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |   .8769231   .4157643     2.11   0.035       .06204    1.691806
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. nnmatch lastgreat coupon1 age gender heightm number, robust(1)
1 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        65
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
   lastgreat |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |   .4615385   .4491061     1.03   0.304    -.4186933     1.34177
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. nnmatch platewaste coupon1 age gender heightm number, robust(1)
1 observations dropped due to treatment variable missing 

Matching estimator:  Average Treatment Effect 

Weighting matrix: inverse variance          Number of obs          =        65
                                            Number of matches  (m) =         1
                                            Number of matches, 
                                              robust std. err. (h) =         1

------------------------------------------------------------------------------
  platewaste |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        SATE |  -.3084615   .1640867    -1.88   0.060    -.6300656    .0131425
------------------------------------------------------------------------------
Matching variables:  age gender heightm number

. 
. *Use the intreg command to obtain robust standard errors in a tobit. This requires the definition of censored variables
. *tobits used to find pseudo r-square
. gen lactualeat=actualeat if actualeat~=1
(7 missing values generated)

. 
. intreg lactualeat actualeat coupon1, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -134.98985  
Iteration 1:   log pseudo-likelihood = -134.47474  
Iteration 2:   log pseudo-likelihood = -134.47394  
Iteration 3:   log pseudo-likelihood = -134.47394  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -132.00646  
Iteration 1:   log pseudo-likelihood = -131.56225  
Iteration 2:   log pseudo-likelihood = -131.56172  
Iteration 3:   log pseudo-likelihood = -131.56172  

Interval regression                               Number of obs   =         66
                                                  Wald chi2(1)    =       6.23
Log pseudo-likelihood = -131.56172                Prob > chi2     =     0.0126

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.209118   .4844305    -2.50   0.013    -2.158584    -.259652
       _cons |   4.016992   .2229109    18.02   0.000     3.580095    4.453889
-------------+----------------------------------------------------------------
    /lnsigma |   .6755312   .1441063     4.69   0.000     .3930881    .9579743
-------------+----------------------------------------------------------------
       sigma |   1.965077   .2831798                      1.481549    2.606411
------------------------------------------------------------------------------

  Observation summary:        59     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. tobit actualeat coupon1, ll(1)

Tobit estimates                                   Number of obs   =         66
                                                  LR chi2(1)      =       5.82
                                                  Prob > chi2     =     0.0158
Log likelihood = -131.56172                       Pseudo R2       =     0.0217

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.209118   .4896954    -2.47   0.016    -2.187107   -.2311291
       _cons |   4.016992   .3344344    12.01   0.000      3.34908    4.684904
-------------+----------------------------------------------------------------
         _se |   1.965077   .1857904           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        59     uncensored observations

. 
. xi: intreg lactualeat actualeat coupon1 gender age heightm number, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -132.57431  
Iteration 1:   log pseudo-likelihood = -132.05191  
Iteration 2:   log pseudo-likelihood = -132.05108  
Iteration 3:   log pseudo-likelihood = -132.05108  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -125.98269  
Iteration 1:   log pseudo-likelihood = -125.63547  
Iteration 2:   log pseudo-likelihood = -125.63543  
Iteration 3:   log pseudo-likelihood = -125.63543  

Interval regression                               Number of obs   =         65
                                                  Wald chi2(5)    =      26.71
Log pseudo-likelihood = -125.63543                Prob > chi2     =     0.0001

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.039221   .4717449    -2.20   0.028    -1.963824   -.1146183
      gender |   .7024092   .7334453     0.96   0.338    -.7351171    2.139935
         age |  -.0321952   .0203235    -1.58   0.113    -.0720286    .0076382
     heightm |   2.974348   1.821157     1.63   0.102    -.5950529     6.54375
      number |   .0206899   .1162336     0.18   0.859    -.2071239    .2485036
       _cons |  -.9075613   2.488133    -0.36   0.715    -5.784213     3.96909
-------------+----------------------------------------------------------------
    /lnsigma |   .6214657   .1468514     4.23   0.000     .3336422    .9092892
-------------+----------------------------------------------------------------
       sigma |   1.861655   .2733866                      1.396044    2.482557
------------------------------------------------------------------------------

  Observation summary:        58     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat coupon1 gender age heightm number, ll(1)

Tobit estimates                                   Number of obs   =         65
                                                  LR chi2(5)      =      12.83
                                                  Prob > chi2     =     0.0250
Log likelihood = -125.63543                       Pseudo R2       =     0.0486

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.039221   .4820057    -2.16   0.035    -2.003376   -.0750663
      gender |   .7024092   .6815482     1.03   0.307    -.6608903    2.065709
         age |  -.0321952    .020794    -1.55   0.127    -.0737894     .009399
     heightm |   2.974348   2.180116     1.36   0.178    -1.386532    7.335229
      number |   .0206899   .1535891     0.13   0.893    -.2865341    .3279138
       _cons |  -.9075613   3.617775    -0.25   0.803    -8.144188    6.329065
-------------+----------------------------------------------------------------
         _se |   1.861655   .1769864           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        58     uncensored observations

. 
. xi: intreg lactualeat actualeat coupon1 gender age heightm number i.day, cluster(party)
i.day             _Iday_1-3           (naturally coded; _Iday_1 omitted)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -132.57431  
Iteration 1:   log pseudo-likelihood = -132.05191  
Iteration 2:   log pseudo-likelihood = -132.05108  
Iteration 3:   log pseudo-likelihood = -132.05108  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -125.85929  
Iteration 1:   log pseudo-likelihood = -125.54393  
Iteration 2:   log pseudo-likelihood = -125.54391  
Iteration 3:   log pseudo-likelihood = -125.54391  

Interval regression                               Number of obs   =         65
                                                  Wald chi2(7)    =      53.92
Log pseudo-likelihood = -125.54391                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.005605   .4950397    -2.03   0.042    -1.975865   -.0353449
      gender |   .7133057   .7454468     0.96   0.339    -.7477431    2.174355
         age |  -.0318593   .0210387    -1.51   0.130    -.0730944    .0093758
     heightm |   3.054409   1.802089     1.69   0.090    -.4776202    6.586439
      number |    .025686   .1188666     0.22   0.829    -.2072882    .2586602
     _Iday_2 |   .0559733    .595399     0.09   0.925    -1.110987    1.222934
     _Iday_3 |  -.1771426   .5899888    -0.30   0.764    -1.333499    .9792141
       _cons |  -1.054903   2.657833    -0.40   0.691    -6.264161    4.154354
-------------+----------------------------------------------------------------
    /lnsigma |   .6195761   .1436743     4.31   0.000     .3379797    .9011726
-------------+----------------------------------------------------------------
       sigma |    1.85814    .266967                      1.402112    2.462489
------------------------------------------------------------------------------

  Observation summary:        58     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat coupon1 gender age heightm number i.day, ll(1)
i.day             _Iday_1-3           (naturally coded; _Iday_1 omitted)

Tobit estimates                                   Number of obs   =         65
                                                  LR chi2(7)      =      13.01
                                                  Prob > chi2     =     0.0718
Log likelihood = -125.54391                       Pseudo R2       =     0.0493

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     coupon1 |  -1.005605   .4895305    -2.05   0.044    -1.985507   -.0257031
      gender |   .7133057   .6817341     1.05   0.300    -.6513334    2.077945
         age |  -.0318593   .0208793    -1.53   0.132    -.0736538    .0099352
     heightm |   3.054409   2.188882     1.40   0.168    -1.327115    7.435933
      number |    .025686   .1538354     0.17   0.868     -.282249     .333621
     _Iday_2 |   .0559733   .6085493     0.09   0.927    -1.162171    1.274117
     _Iday_3 |  -.1771426   .5711665    -0.31   0.758    -1.320457    .9661715
       _cons |  -1.054903   3.683647    -0.29   0.776    -8.428525    6.318718
-------------+----------------------------------------------------------------
         _se |    1.85814   .1767976           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        58     uncensored observations

. 
. * Generating the tobit results for the impact of taste ratings within treatment for table 4
. xi: intreg lactualeat actualeat generalgreat gender age heightm number if coupon1==1, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -57.566969  
Iteration 1:   log pseudo-likelihood = -57.242349  
Iteration 2:   log pseudo-likelihood = -57.241707  
Iteration 3:   log pseudo-likelihood = -57.241707  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -54.874662  
Iteration 1:   log pseudo-likelihood = -54.546371  
Iteration 2:   log pseudo-likelihood = -54.546275  
Iteration 3:   log pseudo-likelihood = -54.546275  

Interval regression                               Number of obs   =         30
                                                  Wald chi2(5)    =      16.88
Log pseudo-likelihood = -54.546275                Prob > chi2     =     0.0047

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.1599318    .168052    -0.95   0.341    -.4893077     .169444
      gender |   .8301118   1.069469     0.78   0.438    -1.266009    2.926232
         age |  -.0304542   .0387814    -0.79   0.432    -.1064645     .045556
     heightm |   3.071463   2.335075     1.32   0.188    -1.505201    7.648126
      number |  -.0685184   .2710664    -0.25   0.800    -.5997988    .4627621
       _cons |  -.8044162   1.814055    -0.44   0.657    -4.359899    2.751066
-------------+----------------------------------------------------------------
    /lnsigma |   .5439299   .1949595     2.79   0.005     .1618163    .9260434
-------------+----------------------------------------------------------------
       sigma |   1.722764   .3358691                      1.175644    2.524501
------------------------------------------------------------------------------

  Observation summary:        26     uncensored observations
                               4  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  generalgreat gender age heightm number if coupon1==1, ll(1)

Tobit estimates                                   Number of obs   =         30
                                                  LR chi2(5)      =       5.39
                                                  Prob > chi2     =     0.3701
Log likelihood = -54.546275                       Pseudo R2       =     0.0471

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.1599318   .1978331    -0.81   0.426    -.5673766     .247513
      gender |   .8301118   .8970466     0.93   0.364     -1.01739    2.677614
         age |  -.0304542   .0293485    -1.04   0.309    -.0908986    .0299901
     heightm |   3.071463   2.464816     1.25   0.224    -2.004921    8.147846
      number |  -.0685184   .2357892    -0.29   0.774    -.5541353    .4170985
       _cons |  -.8044162    4.17883    -0.19   0.849    -9.410878    7.802046
-------------+----------------------------------------------------------------
         _se |   1.722764   .2448476           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          4  left-censored observations at actual~t<=1
                        26     uncensored observations

. 
. xi: intreg lactualeat actualeat firstgreat gender age heightm number if coupon1==1, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -59.186371  
Iteration 1:   log pseudo-likelihood = -58.873374  
Iteration 2:   log pseudo-likelihood = -58.872802  
Iteration 3:   log pseudo-likelihood = -58.872802  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -54.405758  
Iteration 1:   log pseudo-likelihood = -54.091851  
Iteration 2:   log pseudo-likelihood = -54.091761  
Iteration 3:   log pseudo-likelihood = -54.091761  

Interval regression                               Number of obs   =         31
                                                  Wald chi2(5)    =      10.37
Log pseudo-likelihood = -54.091761                Prob > chi2     =     0.0655

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.4572316   .2295469    -1.99   0.046    -.9071353   -.0073278
      gender |   .8971621   .8939485     1.00   0.316    -.8549448    2.649269
         age |   -.022713   .0303418    -0.75   0.454    -.0821819    .0367558
     heightm |    2.27793   1.672658     1.36   0.173    -1.000418    5.556279
      number |   .0122959   .2197225     0.06   0.955    -.4183522     .442944
       _cons |   2.108659   1.667406     1.26   0.206    -1.159396    5.376714
-------------+----------------------------------------------------------------
    /lnsigma |   .4534991   .1624058     2.79   0.005     .1351895    .7718087
-------------+----------------------------------------------------------------
       sigma |    1.57381   .2555959                      1.144754    2.163676
------------------------------------------------------------------------------

  Observation summary:        27     uncensored observations
                               4  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  firstgreat gender age heightm number if coupon1==1, ll(1)

Tobit estimates                                   Number of obs   =         31
                                                  LR chi2(5)      =       9.56
                                                  Prob > chi2     =     0.0886
Log likelihood = -54.091761                       Pseudo R2       =     0.0812

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.4572316   .2078711    -2.20   0.037    -.8845168   -.0299463
      gender |   .8971621   .7666335     1.17   0.253    -.6786756       2.473
         age |   -.022713   .0268752    -0.85   0.406    -.0779558    .0325297
     heightm |    2.27793    2.26414     1.01   0.324    -2.376076    6.931937
      number |   .0122959   .2190333     0.06   0.956    -.4379335    .4625254
       _cons |   2.108659   4.005693     0.53   0.603    -6.125161    10.34248
-------------+----------------------------------------------------------------
         _se |    1.57381   .2190285           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          4  left-censored observations at actual~t<=1
                        27     uncensored observations

. 
. xi: intreg lactualeat actualeat lastgreat gender age heightm number if coupon1==1, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -59.186371  
Iteration 1:   log pseudo-likelihood = -58.873374  
Iteration 2:   log pseudo-likelihood = -58.872802  
Iteration 3:   log pseudo-likelihood = -58.872802  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -55.714653  
Iteration 1:   log pseudo-likelihood = -55.340149  
Iteration 2:   log pseudo-likelihood = -55.339992  
Iteration 3:   log pseudo-likelihood = -55.339992  

Interval regression                               Number of obs   =         31
                                                  Wald chi2(5)    =       8.25
Log pseudo-likelihood = -55.339992                Prob > chi2     =     0.1429

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.2887157   .1969764    -1.47   0.143    -.6747825     .097351
      gender |   .9838352   .9372263     1.05   0.294    -.8530947    2.820765
         age |  -.0298309   .0362777    -0.82   0.411    -.1009338     .041272
     heightm |    2.68085   2.204249     1.22   0.224    -1.639399    7.001099
      number |  -.0004243   .2525348    -0.00   0.999    -.4953834    .4945347
       _cons |   .3073118   1.502607     0.20   0.838    -2.637745    3.252368
-------------+----------------------------------------------------------------
    /lnsigma |   .5069972   .1906195     2.66   0.008     .1333899    .8806045
-------------+----------------------------------------------------------------
       sigma |   1.660298   .3164852                      1.142695    2.412358
------------------------------------------------------------------------------

  Observation summary:        27     uncensored observations
                               4  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  lastgreat gender age heightm number if coupon1==1, ll(1)

Tobit estimates                                   Number of obs   =         31
                                                  LR chi2(5)      =       7.07
                                                  Prob > chi2     =     0.2158
Log likelihood = -55.339992                       Pseudo R2       =     0.0600

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.2887157   .2030282    -1.42   0.167    -.7060461    .1286146
      gender |   .9838352   .8147211     1.21   0.238     -.690848    2.658518
         age |  -.0298309   .0282664    -1.06   0.301    -.0879333    .0282714
     heightm |    2.68085   2.377067     1.13   0.270    -2.205282    7.566982
      number |  -.0004243   .2353331    -0.00   0.999    -.4841585    .4833099
       _cons |   .3073118   4.085244     0.08   0.941    -8.090028    8.704652
-------------+----------------------------------------------------------------
         _se |   1.660298   .2307438           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          4  left-censored observations at actual~t<=1
                        27     uncensored observations

. 
. xi: intreg lactualeat actualeat generalgreat gender age heightm number if coupon1==0, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -70.493962  
Iteration 1:   log pseudo-likelihood = -70.342493  
Iteration 2:   log pseudo-likelihood = -70.342363  
Iteration 3:   log pseudo-likelihood = -70.342363  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -67.984928  
Iteration 1:   log pseudo-likelihood = -67.898225  
Iteration 2:   log pseudo-likelihood = -67.898224  

Interval regression                               Number of obs   =         34
                                                  Wald chi2(5)    =     135.58
Log pseudo-likelihood = -67.898224                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.2977265   .1293055    -2.30   0.021    -.5511606   -.0442924
      gender |    .330049   1.181381     0.28   0.780    -1.985415    2.645513
         age |  -.0344627   .0333578    -1.03   0.302    -.0998428    .0309173
     heightm |   1.970488   3.523411     0.56   0.576    -4.935271    8.876248
      number |   .0084958   .0953815     0.09   0.929    -.1784485    .1954401
       _cons |   3.195483   5.696052     0.56   0.575    -7.968573    14.35954
-------------+----------------------------------------------------------------
    /lnsigma |   .6580254   .2062096     3.19   0.001      .253862    1.062189
-------------+----------------------------------------------------------------
       sigma |   1.930976   .3981858                      1.288994    2.892696
------------------------------------------------------------------------------

  Observation summary:        31     uncensored observations
                               3  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  generalgreat gender age heightm number if coupon1==0, ll(1)

Tobit estimates                                   Number of obs   =         34
                                                  LR chi2(5)      =       4.89
                                                  Prob > chi2     =     0.4297
Log likelihood = -67.898224                       Pseudo R2       =     0.0347

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.2977265   .2412741    -1.23   0.227    -.7911875    .1957345
      gender |    .330049   1.116701     0.30   0.770    -1.953862     2.61396
         age |  -.0344627   .0311081    -1.11   0.277     -.098086    .0291605
     heightm |   1.970488   4.331697     0.45   0.653    -6.888826     10.8298
      number |   .0084958   .2200184     0.04   0.969    -.4414923    .4584838
       _cons |   3.195483   7.534473     0.42   0.675    -12.21424    18.60521
-------------+----------------------------------------------------------------
         _se |   1.930976   .2513579           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          3  left-censored observations at actual~t<=1
                        31     uncensored observations

. 
. xi: intreg lactualeat actualeat firstgreat gender age heightm number if coupon1==0, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -70.493962  
Iteration 1:   log pseudo-likelihood = -70.342493  
Iteration 2:   log pseudo-likelihood = -70.342363  
Iteration 3:   log pseudo-likelihood = -70.342363  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -68.536757  
Iteration 1:   log pseudo-likelihood =  -68.46835  
Iteration 2:   log pseudo-likelihood = -68.468349  

Interval regression                               Number of obs   =         34
                                                  Wald chi2(5)    =     112.55
Log pseudo-likelihood = -68.468349                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.1359516   .1030618    -1.32   0.187     -.337949    .0660457
      gender |   .4129765   1.160461     0.36   0.722    -1.861485    2.687438
         age |  -.0405587   .0293304    -1.38   0.167    -.0980452    .0169277
     heightm |   1.279239   3.469965     0.37   0.712    -5.521768    8.080246
      number |   .0547787   .0814902     0.67   0.501    -.1049391    .2144965
       _cons |   3.403465   4.995745     0.68   0.496    -6.388015    13.19495
-------------+----------------------------------------------------------------
    /lnsigma |   .6723491   .2093639     3.21   0.001     .2620033    1.082695
-------------+----------------------------------------------------------------
       sigma |   1.958833   .4101091                      1.299531    2.952626
------------------------------------------------------------------------------

  Observation summary:        31     uncensored observations
                               3  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  firstgreat gender age heightm number if coupon1==0, ll(1)

Tobit estimates                                   Number of obs   =         34
                                                  LR chi2(5)      =       3.75
                                                  Prob > chi2     =     0.5862
Log likelihood = -68.468349                       Pseudo R2       =     0.0266

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.1359516   .2221581    -0.61   0.545     -.590316    .3184127
      gender |   .4129765   1.134032     0.36   0.718    -1.906378    2.732331
         age |  -.0405587   .0310758    -1.31   0.202    -.1041158    .0229983
     heightm |   1.279239   4.423137     0.29   0.774    -7.767092    10.32557
      number |   .0547787    .220832     0.25   0.806    -.3968734    .5064308
       _cons |   3.403465   8.062815     0.42   0.676    -13.08684    19.89377
-------------+----------------------------------------------------------------
         _se |   1.958833   .2551551           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          3  left-censored observations at actual~t<=1
                        31     uncensored observations

. 
. xi: intreg lactualeat actualeat lastgreat gender age heightm number if coupon1==0, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -70.493962  
Iteration 1:   log pseudo-likelihood = -70.342493  
Iteration 2:   log pseudo-likelihood = -70.342363  
Iteration 3:   log pseudo-likelihood = -70.342363  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -67.238819  
Iteration 1:   log pseudo-likelihood = -67.152989  
Iteration 2:   log pseudo-likelihood = -67.152988  

Interval regression                               Number of obs   =         34
                                                  Wald chi2(5)    =      25.81
Log pseudo-likelihood = -67.152988                Prob > chi2     =     0.0001

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.4262349   .2745109    -1.55   0.120    -.9642664    .1117966
      gender |   .5096096   1.128747     0.45   0.652    -1.702693    2.721912
         age |  -.0213106   .0364254    -0.59   0.559    -.0927032    .0500819
     heightm |   .6598307   3.788664     0.17   0.862    -6.765815    8.085476
      number |  -.0045942   .1212458    -0.04   0.970    -.2422316    .2330431
       _cons |   5.868176   7.078943     0.83   0.407    -8.006297    19.74265
-------------+----------------------------------------------------------------
    /lnsigma |   .6354151   .1820621     3.49   0.000       .27858    .9922502
-------------+----------------------------------------------------------------
       sigma |   1.887806   .3436978                      1.321252    2.697297
------------------------------------------------------------------------------

  Observation summary:        31     uncensored observations
                               3  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  lastgreat gender age heightm number if coupon1==0, ll(1)

Tobit estimates                                   Number of obs   =         34
                                                  LR chi2(5)      =       6.38
                                                  Prob > chi2     =     0.2711
Log likelihood = -67.152988                       Pseudo R2       =     0.0453

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.4262349    .242383    -1.76   0.089    -.9219638     .069494
      gender |   .5096096   1.084966     0.47   0.642    -1.709396    2.728615
         age |  -.0213106   .0320008    -0.67   0.511    -.0867596    .0441384
     heightm |   .6598307   4.269605     0.15   0.878    -8.072493    9.392154
      number |  -.0045942   .2114738    -0.02   0.983    -.4371067    .4279183
       _cons |   5.868176    7.65993     0.77   0.450    -9.798141    21.53449
-------------+----------------------------------------------------------------
         _se |   1.887806   .2454961           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          3  left-censored observations at actual~t<=1
                        31     uncensored observations

. 
. xi: intreg lactualeat actualeat generalgreat coupon1 gender age heightm number, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -130.70594  
Iteration 1:   log pseudo-likelihood = -130.17408  
Iteration 2:   log pseudo-likelihood =  -130.1732  
Iteration 3:   log pseudo-likelihood =  -130.1732  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -123.25144  
Iteration 1:   log pseudo-likelihood = -122.88416  
Iteration 2:   log pseudo-likelihood = -122.88413  
Iteration 3:   log pseudo-likelihood = -122.88413  

Interval regression                               Number of obs   =         64
                                                  Wald chi2(6)    =      32.51
Log pseudo-likelihood = -122.88413                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.2334164    .103695    -2.25   0.024    -.4366549   -.0301779
     coupon1 |  -.9005819    .427056    -2.11   0.035    -1.737596   -.0635676
      gender |   .6018189   .7974227     0.75   0.450     -.961101    2.164739
         age |  -.0309033   .0212314    -1.46   0.146    -.0725161    .0107096
     heightm |   2.908627   1.728108     1.68   0.092    -.4784017    6.295655
      number |  -.0008264   .1203672    -0.01   0.995    -.2367418    .2350889
       _cons |   .7978754   2.129345     0.37   0.708    -3.375564    4.971315
-------------+----------------------------------------------------------------
    /lnsigma |   .6127647   .1455693     4.21   0.000     .3274541    .8980753
-------------+----------------------------------------------------------------
       sigma |   1.845527    .268652                      1.387431    2.454874
------------------------------------------------------------------------------

  Observation summary:        57     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  generalgreat coupon1 gender age heightm number, ll(1)

Tobit estimates                                   Number of obs   =         64
                                                  LR chi2(6)      =      14.58
                                                  Prob > chi2     =     0.0238
Log likelihood = -122.88413                       Pseudo R2       =     0.0560

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
generalgreat |  -.2334164   .1502777    -1.55   0.126    -.5342298    .0673971
     coupon1 |  -.9005819    .487756    -1.85   0.070    -1.876932    .0757678
      gender |   .6018189   .7027722     0.86   0.395    -.8049325     2.00857
         age |  -.0309033   .0208459    -1.48   0.144    -.0726308    .0108243
     heightm |   2.908627   2.170416     1.34   0.185    -1.435932    7.253186
      number |  -.0008264   .1529512    -0.01   0.996    -.3069915    .3053386
       _cons |   .7978754   3.750134     0.21   0.832    -6.708834    8.304585
-------------+----------------------------------------------------------------
         _se |   1.845527     .17692           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        57     uncensored observations

. 
. xi: intreg lactualeat actualeat firstgreat coupon1 gender age heightm number, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -132.57431  
Iteration 1:   log pseudo-likelihood = -132.05191  
Iteration 2:   log pseudo-likelihood = -132.05108  
Iteration 3:   log pseudo-likelihood = -132.05108  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -124.43824  
Iteration 1:   log pseudo-likelihood = -124.10472  
Iteration 2:   log pseudo-likelihood =  -124.1047  
Iteration 3:   log pseudo-likelihood =  -124.1047  

Interval regression                               Number of obs   =         65
                                                  Wald chi2(6)    =      59.14
Log pseudo-likelihood =  -124.1047                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.2648676    .139051    -1.90   0.057    -.5374025    .0076673
     coupon1 |  -.8976902   .4426436    -2.03   0.043    -1.765256   -.0301246
      gender |   .6668256   .7051784     0.95   0.344    -.7152986     2.04895
         age |  -.0301176   .0198516    -1.52   0.129     -.069026    .0087908
     heightm |   2.455098   1.424714     1.72   0.085    -.3372901    5.247487
      number |   .0013627   .1172535     0.01   0.991    -.2284499    .2311753
       _cons |   1.777982   1.503205     1.18   0.237    -1.168245    4.724209
-------------+----------------------------------------------------------------
    /lnsigma |   .5974632   .1509706     3.96   0.000     .3015663    .8933601
-------------+----------------------------------------------------------------
       sigma |   1.817502   .2743894                      1.351975    2.443326
------------------------------------------------------------------------------

  Observation summary:        58     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  firstgreat coupon1 gender age heightm number, ll(1)

Tobit estimates                                   Number of obs   =         65
                                                  LR chi2(6)      =      15.89
                                                  Prob > chi2     =     0.0143
Log likelihood =  -124.1047                       Pseudo R2       =     0.0602

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  firstgreat |  -.2648676   .1498637    -1.77   0.082    -.5647441    .0350089
     coupon1 |  -.8976902   .4777099    -1.88   0.065    -1.853586    .0582052
      gender |   .6668256   .6652693     1.00   0.320    -.6643752    1.998026
         age |  -.0301176   .0203673    -1.48   0.145    -.0708725    .0106373
     heightm |   2.455098   2.150433     1.14   0.258    -1.847908    6.758105
      number |   .0013627   .1503331     0.01   0.993    -.2994532    .3021786
       _cons |   1.777982   3.840237     0.46   0.645    -5.906314    9.462278
-------------+----------------------------------------------------------------
         _se |   1.817502   .1726439           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        58     uncensored observations

. 
. xi: intreg lactualeat actualeat lastgreat coupon1 gender age heightm number, cluster(party)

Fitting constant-only model:

Iteration 0:   log pseudo-likelihood = -132.57431  
Iteration 1:   log pseudo-likelihood = -132.05191  
Iteration 2:   log pseudo-likelihood = -132.05108  
Iteration 3:   log pseudo-likelihood = -132.05108  

Fitting full model:

Iteration 0:   log pseudo-likelihood = -123.44396  
Iteration 1:   log pseudo-likelihood = -123.07252  
Iteration 2:   log pseudo-likelihood = -123.07249  
Iteration 3:   log pseudo-likelihood = -123.07249  

Interval regression                               Number of obs   =         65
                                                  Wald chi2(6)    =      37.04
Log pseudo-likelihood = -123.07249                Prob > chi2     =     0.0000

                            (standard errors adjusted for clustering on party)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.3370698   .1316616    -2.56   0.010    -.5951219   -.0790177
     coupon1 |  -.9489333   .3971582    -2.39   0.017    -1.727349   -.1705176
      gender |   .7922801   .7209111     1.10   0.272    -.6206797     2.20524
         age |  -.0249257   .0196389    -1.27   0.204    -.0634172    .0135658
     heightm |   2.190277   1.663872     1.32   0.188    -1.070852    5.451406
      number |   .0284243   .1107564     0.26   0.797    -.1886543     .245503
       _cons |   2.295463    2.27662     1.01   0.313     -2.16663    6.757556
-------------+----------------------------------------------------------------
    /lnsigma |   .5827737   .1383205     4.21   0.000     .3116705    .8538769
-------------+----------------------------------------------------------------
       sigma |   1.790999   .2477319                      1.365705    2.348735
------------------------------------------------------------------------------

  Observation summary:        58     uncensored observations
                               7  left-censored observations
                               0 right-censored observations
                               0       interval observations

. xi: tobit actualeat  lastgreat coupon1 gender age heightm number, ll(1)

Tobit estimates                                   Number of obs   =         65
                                                  LR chi2(6)      =      17.96
                                                  Prob > chi2     =     0.0063
Log likelihood = -123.07249                       Pseudo R2       =     0.0680

------------------------------------------------------------------------------
   actualeat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lastgreat |  -.3370698   .1466479    -2.30   0.025    -.6305115   -.0436282
     coupon1 |  -.9489333   .4660176    -2.04   0.046    -1.881432   -.0164342
      gender |   .7922801   .6579109     1.20   0.233    -.5241967    2.108757
         age |  -.0249257    .020294    -1.23   0.224    -.0655339    .0156826
     heightm |   2.190277    2.12713     1.03   0.307      -2.0661    6.446654
      number |   .0284243   .1479753     0.19   0.848    -.2676736    .3245223
       _cons |   2.295463   3.744483     0.61   0.542     -5.19723    9.788156
-------------+----------------------------------------------------------------
         _se |   1.790999    .169914           (Ancillary parameter)
------------------------------------------------------------------------------

  Obs. summary:          7  left-censored observations at actual~t<=1
                        58     uncensored observations

. 
end of do-file

. exit, clear
